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基于多区域人群的上海公交走廊出行行为 被引量:5

Travel Behavior Analysis of Different-regional Passengers for Public Transport Corridor in Shanghai
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摘要 基于上海市公共交通走廊内的乘客出行调查,利用离散选择理论,建立了现状调查/假设意愿调查(RP/SP)融合数据的Nested Logit模型.通过模型参数标定、敏感性分析从定性、定量两个角度研究了在城市公交走廊内,来自不同区域的出行者对于公共交通方式的出行行为及影响因素;在此基础上,分析了模型在不同空间范围内的转移适用性;最后,通过算例进行分析和验证.通过研究可知,在城市公交走廊内,影响出行者选择行为的因素不尽相同,其区域差异性不容忽视;其次,不同区域的出行者对于各公交方式的偏好存在较大差异;再次,不同区域的出行者在走廊内选择交通方式时,对于同一影响因素的敏感性有所不同.从数据获取、模型建立、标定分析及仿真验证四个步骤逐次展开,提出了针对不同区域出行者在城市公交走廊选择行为的基本方法和必要性,对未来城市公共交通走廊的规划和改进提供新的思路和方向. Through the passenger behavior survey of public transport corridor in Shanghai,this paper proposes a revealed preference/stated preference(RP/SP)combined Nested Logit model.Based upon the discrete choice theory,the proposed model analyzes qualitatively and quantitatively the travel behavior of different-regional passengers and some factors which influence their behavior.And then the paper researches the spatial transferability of this model.Finally,the model aims to simulate the travel behavior of different-regional passengers upon different policy scenarios.The results shows that in urban public transportation corridor,the factors which influence passenger travel behavior are different because they come from different regions.Secondly,for different-regional passengers,their preference of public mode may also be different. Thirdly, there are differences among the sensibilities of different-regional passengers to some factors which influence their travel behavior. Relying on data collection,modeling,parameter calibration and simulation,the paper provides a method of analyzing travel behavior for different-regional passengers,which may be a useful tool for function optimization and efficiency enhancement of urban public transport corridor.
作者 狄迪 杨东援
出处 《同济大学学报(自然科学版)》 EI CAS CSCD 北大核心 2016年第3期369-376,共8页 Journal of Tongji University:Natural Science
关键词 多区域人群 公交走廊 出行行为 现状调查/假设意愿调查(RP/SP)数据融合 Nested LOGIT模型 different-regional passengers public transport corridor travel behavior revealed preference/stated preference(RP/SP)combined Nested Logit model
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参考文献10

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